Joining twoday as a Lead Consultant this week, I felt that classic "new job" mix of excitement and being a little bit overwhelmed. There's so much to learn—tools, processes, client expectations—and I wanted to hit the ground not just running, but sprinting.

Instead of drowning in onboarding material, I chose a different path: I made AI tools my onboarding buddy, my personal analyst, project planner, and sparring partner. TL;DR: This could easily become a series of articles diving into how I use and manage various AI agents, how I build them and what they deliver, but here's what I gained—fast—in my first five days at twoday: getting up to speed with my team, understanding and building an execution plan for my client, running a full product assessment, and letting my AI agents work for me.

The First Big Win: Team and Focus

As a new employee, my "profile" had almost no information—no documents drafted, no SharePoint pages read or written. But in an organization with open document sharing, updated Org. Explorer, and other Microsoft tools, there's a wealth of information available if you know how to tap into it. That's why I made Copilot, Perplexity, Claude, and ChatGPT my buddies this week—each with its own strengths, limitations, and compliance restrictions. To get up to speed, I focused on understanding the core of my team: Cloud Platform Security.

Prompts I Used

"You are the expert in my domain, 'Cloud Platform and Security.' List the most important aspects my manager, reporting line and coworkers are working on, and what I should be up to date with." After refining my ask, I requested a summary of current priorities in the group and strategic focus areas important for my role at twoday, along with references and key documents for deeper exploration. The output gave me recent insights, focus points, responsibilities, and even introductions to my teammates, linking their work to twoday's strategy. This was the shortcut I needed to truly get started. (Yes, Copilot has introduced me to all of you. Nice to AI-meet)

Getting Started with Clients and My Own Agents

As consultants, we often produce various artifacts—reports, presentations, project plans. Early at twoday, I learned about a potential new partner, complete with deliverables and contractual obligations if we land the contract. Using Copilot Studio, I built my own project plan agent. With just basic inputs, it created a structured execution plan and a PowerPoint for client reporting. The first draft took under an hour and can significantly speed up onboarding, execution, and client success.

Another agent I use is my AI Use Case Agent. People often ask, "What can I use AI/Copilot for, and how will it help me?" The real question is about business justification and ROI. Our solution is to run sessions with clients to uncover use cases, build strong business cases, and raise organizational awareness—before beginning implementation. There's a wealth of research, best-practice examples, and proven business cases that we can leverage to help clients accelerate their own journeys and justify AI adoption.

Currently, my agent taps into external global data sources for role descriptions and responsibilities. I ask it to tailor its analysis to my partner's industry, providing role- and industry-specific insights on work areas ripe for human-led or fully automated AI improvements, complete with recommendations and impact assessments. As I continue, I'll refine the agent to analyze company-specific role descriptions and propose even more relevant AI use cases. It's a first version—always room for improvement—but already a valuable tool for me.

Be Smart: Leverage Others' Work

Why reinvent the wheel when you can build upon what others have already done? For example, I attended a Microsoft webinar on Tuesday where they briefly mentioned a tool for boosting Copilot adoption and shared a GitHub repository. Rather than sifting through code (I'm not a data engineer!), I used Claude to analyze the repository for me, explaining the UI, UX, the user problems it addresses, and how we might adapt it for our own clients and strategic goals. This let me quickly assess whether and how we could scale the solution across markets, tailoring it to industry needs and roles.

With a few targeted prompts, I was able to research like a pro—exploring product technology, use cases, and how we might implement and scale solutions for our clients. This is the power of leveraging AI for product assessment and insights analytics.

Product Assessment with AI

Years of knowledge, documentation, and background always inform every solution, service, and decision. When you're new, you have to rely on your skills and tools. My background in Product Management means I know the key questions for product assessment and strategy. So, I outlined my essential product assessment questions and had my AI agents—Researcher, Analyst, and Copilot Chat—answer them with the information available. By lunchtime today, I had an analysis based on all accessible data, which I used to inform my own thoughts and questions. There are still open questions about aligning with twoday's strategy and offerings, but the AI-generated analysis gave me a meeting brief and a foundation for further exploration. I might even build my own assessment agent—let's see where this leads!

Takeaways: Amplify Your Expertise

Why I'm Sharing This

Whether you're new in a company or just curious, give it a try. Experiment. Ask questions. Use AI to make your work easier and more impactful. Spend more time on what's fun and innovative. AI can never take away your creativity or your ability to innovate and think strategically. So let AI do its best—and let yourself do yours.

Disclaimer: Yes, I made Copilot and other AI tools read through the whole article, edit wording, structure, etc. to help me. What can I say. AI tools are my partner in crime.